
Data Systems Architect
3 days ago
Lead the development of scalable GenAI-powered systems. Drive solution architecture, mentor junior engineers, and deliver production-ready applications.
- Design intelligent workflows that leverage large language models (LLMs), vector-based retrieval, and multi-agent orchestration frameworks.
- Architect and optimize prompt workflows for high-accuracy and cost-efficient solutions.
Key Responsibilities:
- Lead the design and deployment of GenAI systems leveraging LLMs, retrieval pipelines, and orchestration frameworks.
- Optimize workflow performance using chaining, templating, and context control techniques.
- Develop embedding-based retrieval systems using vector databases and context-aware generation techniques.
- Collaborate with product owners and engineering leads to align solution architecture with business objectives.
- Guide and mentor junior engineers on best practices in prompt design, token optimization, security controls, and observability patterns.
- Maintain strong CI/CD practices using version-controlled workflows and cloud-native deployment pipelines.
Qualifications:
- 4+ years of experience in AI/ML solution delivery, with a strong focus on GenAI or LLM-integrated systems.
- Expertise in Python (v3.11+) with deep familiarity in LLM APIs, embedding generation, vector-based search, and modular pipeline design.
- Proven experience in building and deploying prompt-driven applications at scale.
- Solid understanding of agent orchestration patterns, multi-agent task flows, and context layering techniques.
- Hands-on experience in cloud-native delivery (preferably Azure), including containerization, CI/CD, and monitoring.
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